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Interpreting and coding causal relationships for quality and safety using ICD-11.
Januel, Jean-Marie; Southern, Danielle A; Ghali, William A.
Afiliación
  • Januel JM; Department of Biomedical Informatics, Rouen University Hospital, 37 Boulevard Gambetta, Rouen, 76000, France. jean-marie.januel@hotmail.com.
  • Southern DA; Translational Innovation in Medicine and Complexity (TIMC) Laboratory, Deep Care research chair, Multidisciplinary Institute in Artificial Intelligence, Université Grenoble Alpes (UGA) and Centre National de Recherche Scientifique (CNRS), Grenoble, France. jean-marie.januel@hotmail.com.
  • Ghali WA; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada.
BMC Med Inform Decis Mak ; 21(Suppl 6): 385, 2023 11 16.
Article en En | MEDLINE | ID: mdl-37974148
Many circumstances necessitate judgments regarding causation in health information systems, but these can be tricky in medicine and epidemiology. In this article, we reflect on what the ICD-11 Reference Guide provides on coding for causation and judging when relationships between clinical concepts are causal. Based on the use of different types of codes and the development of a new mechanism for coding potential causal relationships, the ICD-11 provides an in-depth transformation of coding expectations as compared to ICD-10. An essential part of the causal relationship interpretation relies on the presence of "connecting terms," key elements in assessing the level of certainty regarding a potential relationship and how to proceed in coding a causal relationship using the new ICD-11 coding convention of postcoordination (i.e., clustering of codes). In addition, determining causation involves using documentation from healthcare providers, which is the foundation for coding health information. The coding guidelines and examples (taken from the quality and patient safety domain) presented in this article underline how new ICD-11 features and coding rules will enhance future health information systems and healthcare.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Clasificación Internacional de Enfermedades / Documentación Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Clasificación Internacional de Enfermedades / Documentación Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Francia